Prediction trajectory of moving target based on parameter identify in RLS filtering with forget factor

Yili Yin; Yan Tian; Zhang Li

doi:10.1117/12.2202377

8 October 2015 Prediction trajectory of moving target based on parameter identify in RLS filtering with forget factor

Yili Yin, Yan Tian, Zhang Li

Proceedings Volume 9677, AOPC 2015: Optical Test, Measurement, and Equipment; 967725 (2015) https://doi.org/10.1117/12.2202377
Event: Applied Optics and Photonics China (AOPC2015), 2015, Beijing, China

Abstract

A moving target should be missing from a photoelectric theodolite tracker, when the clouds and other special conditions encountered in the course of a theodolite tracking a moving object, and this condition should cause the interruption of tracking process. In view of this problem, an algorithm based on the frame of parameter identification and rolling prediction to trajectory was presented to predicting the target trajectory when it missing. Firstly, the article makes a specification of photoelectric theodolite and it operating mechanism detailed. The reasons of flying target imaging disappear from the field of theodolite telescope and the traditional solution to this problem, the least square curve fitting of trajectory quadratic function of time, were narrated secondly. The algorithm based on recursive least square with forget factor, identify the parameters of target motion using the data of position from single theodolite, then the forecasting trajectory of moving targets was presented afterwards ,in the filtering approach of past data rolling smooth with the weight of last procedure. By simulation with tracking moving targets synthetic corner from a real tracking routine of photoelectric theodolite, the algorithm was testified, and the simulation of curve fitting a quadratic function of time was compared at the last part.

Citation Download Citation

Yili Yin, Yan Tian, and Zhang Li "Prediction trajectory of moving target based on parameter identify in RLS filtering with forget factor", Proc. SPIE 9677, AOPC 2015: Optical Test, Measurement, and Equipment, 967725 (8 October 2015); https://doi.org/10.1117/12.2202377

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